A graph-based methodology for constructing computational models that automates adjoint-based sensitivity analysis

V Gandarillas, AJ Joshy, MZ Sperry, AK Ivanov… - Structural and …, 2024 - Springer
The adjoint method provides an efficient way to compute sensitivities for system models with
a large number of inputs. However, implementing the adjoint method requires significant …

Slang. d: Fast, modular and differentiable shader programming

SP Bangaru, L Wu, TM Li, J Munkberg… - ACM Transactions on …, 2023 - dl.acm.org
We introduce SLANG. D, an extension to the Slang shading language that incorporates first-
class automatic differentiation support. The new shading language allows us to transform a …

MITgcm-AD v2: Open source tangent linear and adjoint modeling framework for the oceans and atmosphere enabled by the Automatic Differentiation tool Tapenade

SS Gaikwad, SHK Narayanan, L Hascoet… - Future Generation …, 2024 - Elsevier
Abstract The Massachusetts Institute of Technology General Circulation Model (MITgcm) is
widely used by the climate science community to simulate planetary atmosphere and ocean …

A taxonomy of automatic differentiation pitfalls

J Hückelheim, H Menon, W Moses… - … : Data Mining and …, 2024 - Wiley Online Library
Automatic differentiation is a popular technique for computing derivatives of computer
programs. While automatic differentiation has been successfully used in countless …

Differentiable solver for time-dependent deformation problems with contact

Z Huang, DC Tozoni, A Gjoka, Z Ferguson… - ACM Transactions on …, 2024 - dl.acm.org
We introduce a general differentiable solver for time-dependent deformation problems with
contact and friction. Our approach uses a finite element discretization with a high-order time …

Juliqaoa: Fast, flexible qaoa simulation

J Golden, A Baertschi, D O'Malley, E Pelofske… - Proceedings of the SC' …, 2023 - dl.acm.org
We introduce JuliQAOA, a simulation package specifically built for the Quantum Alternating
Operator Ansatz (QAOA). JuliQAOA does not require a circuit-level description of QAOA …

Understanding automatic differentiation pitfalls

J Hückelheim, H Menon, W Moses… - arxiv preprint arxiv …, 2023 - arxiv.org
Automatic differentiation, also known as backpropagation, AD, autodiff, or algorithmic
differentiation, is a popular technique for computing derivatives of computer programs …

Automatic Differentiation for Explicitly Correlated MP2

EC Mitchell, JM Turney… - Journal of Chemical …, 2024 - ACS Publications
Automatic differentiation (AD) offers a route to achieve arbitrary-order derivatives of
challenging wave function methods without the use of analytic gradients or response theory …

Automatic adjoint-based inversion schemes for geodynamics: reconstructing the evolution of Earth's mantle in space and time

S Ghelichkhan, A Gibson, DR Davies… - Geoscientific Model …, 2024 - gmd.copernicus.org
Reconstructing the thermo-chemical evolution of Earth's mantle and its diverse surface
manifestations is a widely recognised grand challenge for the geosciences. It requires the …

[HTML][HTML] Simplifying FFT-based methods for solid mechanics with automatic differentiation

M Pundir, DS Kammer - Computer Methods in Applied Mechanics and …, 2025 - Elsevier
Abstract Fast-Fourier Transform (FFT) methods have been widely used in solid mechanics to
address complex homogenization problems. However, current FFT-based methods face …